Smart City Gnosys

Smart city article details

Title The Journey To Cloud As A Continuum: Opportunities, Challenges, And Research Directions
ID_Doc 55982
Authors Hasan M.M.; Sultana T.; Hossain M.D.; Mandal A.K.; Ngo T.-T.; Lee G.-W.; Huh E.-N.
Year 2025
Published ICT Express
DOI http://dx.doi.org/10.1016/j.icte.2025.04.015
Abstract The rapid development of the Internet of Things (IoT) has driven a significant shift in computing architectures, leading to the rise of the cloud continuum—a flexible framework that combines cloud services with edge and fog computing. While existing survey papers have contributed valuable insights, they often focus narrowly on specific aspects of the continuum or do not fully address its evolving complexities. These limitations underscore the need for a comprehensive and up-to-date analysis of the field. This study bridges these gaps by presenting an extensive review of the cloud continuum, covering its role in enhancing resource management, improving real-time data processing, integrating machine learning approaches, and optimizing user experiences across diverse applications. We examine how edge devices, fog nodes, and cloud infrastructures synergize to enable decentralized data processing, reducing latency in critical areas such as smart cities, healthcare, and autonomous vehicles. Additionally, this study explores the integration of machine learning across edge, fog, and cloud layers, with a focus on inference and distributed learning methods. By highlighting how these technologies enhance efficiency, scalability, and intelligent decision-making, this review provides a holistic perspective on the cloud continuum. Our analysis offers valuable insights into future research directions, emphasizing innovations that can drive next-generation computing systems toward greater efficiency and adaptability. © 2025 The Authors
Author Keywords Distributed computing; Edge computing; Fog computing; Inference; IoT; Machine learning


Similar Articles


Id Similarity Authors Title Published
21815 View0.912Murthy V.S.N.; Kumari R.; Goyal M.; Dubey P.; Meenakshi; Manikandan S.; Ramesh P.Edge-Ai In Iot: Leveraging Cloud Computing And Big Data For Intelligent Decision-MakingJournal of Information Systems Engineering and Management, 10 (2025)
27178 View0.912Prerna; Sharma S.From Data To Decisions: Cloud, Iot, And Ai IntegrationIntegration of Cloud Computing and IoT: Trends, Case Studies and Applications (2024)
32182 View0.907Kuchuk H.; Malokhvii E.Integration Of Iot With Cloud, Fog, And Edge Computing: A ReviewAdvanced Information Systems, 8, 2 (2024)
30629 View0.9Asha A.; Rajeshkumar L.; Pandi V.S.; Shobana D.; Lakshmi Priya J.; Dayanidhy M.Implementing Cloud Computing With Internet Of Things (Iot) Technologies: Novel Approaches To Data Management And Service Delivery Innovation2024 Global Conference on Communications and Information Technologies, GCCIT 2024 (2024)
21828 View0.899Belcastro L.; Marozzo F.; Orsino A.; Talia D.; Trunfio P.Edge-Cloud Continuum Solutions For Urban Mobility Prediction And PlanningIEEE Access, 11 (2023)
60648 View0.898Belcastro L.; Marozzo F.; Orsino A.; Talia D.; Trunfio P.Using The Compute Continuum For Data Analysis: Edge-Cloud Integration For Urban MobilityProceedings - 2023 31st Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP 2023 (2023)
55549 View0.898Alli A.A.; Alam M.M.The Fog Cloud Of Things: A Survey On Concepts, Architecture, Standards, Tools, And ApplicationsInternet of Things (Netherlands), 9 (2020)
13107 View0.896Krishnappa M.S.; Jayabalan D.; Harve B.M.; Jayaram V.; Bidkar D.M.; Veerapaneni P.K.; Gejjegondanahalli V.Y.Building The Future Of Iot: Cloud Platforms, Integration Challenges, And Emerging Applications2024 International Conference on Computer and Applications, ICCA 2024 (2024)
14842 View0.895Grzesik P.; Mrozek D.Combining Machine Learning And Edge Computing: Opportunities, Challenges, Platforms, Frameworks, And Use CasesElectronics (Switzerland), 13, 3 (2024)
5251 View0.892Hoffpauir K.; Simmons J.; Schmidt N.; Pittala R.; Briggs I.; Makani S.; Jararweh Y.A Survey On Edge Intelligence And Lightweight Machine Learning Support For Future Applications And ServicesJournal of Data and Information Quality, 15, 2 (2023)